def _get_test_and_train_set(input_dir,
min_num_images_per_label,
split_ratio=0.7):
dataset = get_dataset(input_dir)
dataset = filter_dataset(dataset,
min_images_per_label=min_num_images_per_label)
train_set, test_set = split_dataset(dataset, split_ratio=split_ratio)
return train_set, test_set
def _get_test_and_train_set(input_dir, min_num_images_per_label, split_ratio=0.7):
"""
Load train and test dataset. Classes with < :param min_num_images_per_label will be filtered out.
:param input_dir:
:param min_num_images_per_label:
:param split_ratio:
:return:
"""
dataset = get_dataset(input_dir)
dataset = filter_dataset(dataset, min_images_per_label=min_num_images_per_label)
train_set, test_set = split_dataset(dataset, split_ratio=split_ratio)
return train_set, test_set
